7月5日，中金公司连续第七年成功承办2024世界人工智能大会——投融资主题论坛。本届论坛 以"AI规模新经济"为主题，探索通用人工智能产业发展及投融资趋势，纵论产投融合促进新质生产力发 展。本次大会汇聚国内外人工智能等科技前沿领域的著名专家学者、知名投资人士和头部人工智能企业 家代表，共同探讨以全球智慧凝聚创新力量，助力科技创新产业发展。 为把握人工智能（AI）带来的机遇和挑战，中金公司充分调动中金研究院、研究部的研究力量， 对人工智能相关的经济问题进行了深入研究，在本次论坛上重磅推出最新研究成果—《AI经济学》， 力图为各领域的企业和投资者拓展视野，理解当下真实情境，预见未来发展大势提供研究智慧和力量。 此外，本次论坛还邀请2011年诺贝尔经济学奖得主，纽约大学经济学教授，斯坦福大学胡佛研究所 资深研究员托马斯·萨金特，他认为，未来，AI等智能技术发展将呈现出规模报酬递增和成本递减的趋 势，有助于降低整体经济运行过程中的信息摩擦和交易成本。在计算机产业发达的领先经济体中，尤其 是中国和美国，较低成本的软件和算力将帮助智能技术释放更多增长动能，包括帮助中小企业高效、快 速、低成本地开展业务。 中金研究重磅发布 ...

Group 1 - The event "AI + Business Applications" was held in Xi'an, aiming to create a significant platform for AI commercial application display and industry connection in the northwest region of China [1] - The event featured keynote speeches from industry elites and academic experts, discussing the role of AI technology in economic development, industrial upgrading, and talent cultivation [2] - Notable presentations included topics such as "Commercial Reconstruction in the Era of Large Models" and "Embodied Intelligence: The Next Generation of AI Commercialization" [2] Group 2 - The AI China Development Alliance Xi'an Forum was held alongside the event, showcasing the latest achievements and broad prospects of AI technology in commercial applications [2] - The establishment of the "AI Venture Capital Alliance" was initiated by ten organizations, including the Shaanxi Provincial Venture Capital Association and the National Supercomputing Center (Xi'an) [2]

Core Viewpoint - The emergence of DeepSeek challenges traditional beliefs about AI model development, demonstrating that a financial startup from China can innovate in AI, contrary to the notion that only large tech companies or research institutions can do so [1][4][5]. Group 1: AI Economics: Scaling Laws vs. Scale Effects - DeepSeek's success indicates a shift in understanding the barriers to AI model development, particularly reducing the constraints of computational power through algorithm optimization [8][9]. - Scaling laws suggest that increasing model parameters, training data, and computational resources leads to diminishing returns in AI performance, while scale effects highlight that larger scales can reduce unit costs and improve efficiency [10][11]. - The interplay between scaling laws and scale effects is crucial for understanding DeepSeek's breakthrough, as algorithmic advancements can enhance the marginal returns of computational investments [12][14]. Group 2: Latecomer Advantage vs. First-Mover Advantage - The distinction between scaling laws and scale effects provides insights into the competitive landscape of AI, where latecomers like China can potentially catch up due to higher marginal returns on resource investments [16][22]. - The AI development index shows that the U.S. and China dominate the global AI landscape, with both countries possessing significant scale advantages, albeit in different areas [18][22]. - The competition between the U.S. and China in AI is characterized by differing strengths, with the U.S. focusing on computational resources and China leveraging its talent pool and application scenarios [19][22]. Group 3: Open Source Promoting External Scale Economies - DeepSeek's open-source model reduces commercial barriers, facilitating broader adoption and innovation in AI applications, which can accelerate the "AI+" process [24][26]. - The open-source approach allows for greater external scale economies, benefiting a wider range of participants compared to closed-source models, which tend to concentrate profits among fewer entities [25][28]. - The potential market size for AI applications is estimated to be about twice that of the computational and model layers combined, indicating significant growth opportunities [27]. Group 4: Innovation Development: From Supply and Assets to Demand and Talent - The success of DeepSeek raises questions about the role of traditional research institutions in innovation, suggesting that market-driven demands may lead to more successful outcomes in technology development [30][31]. - The integration of technological and industrial innovation is essential for sustainable growth, emphasizing the need for a shift from a supply-side focus to a demand-side approach that values talent and market needs [32][33]. - The importance of talent incentives and a diverse innovation ecosystem is highlighted, as smaller firms may be more agile in pursuing disruptive innovations compared to larger corporations [34][36]. Group 5: From Fintech to Tech Finance - The relationship between finance and technology is re-evaluated, with the success of DeepSeek illustrating how financial firms can leverage technological advancements to enhance their competitive edge [36][39]. - The role of capital markets in fostering innovation ecosystems is emphasized, suggesting that a diverse range of participants is necessary for achieving external scale economies [38][39].